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Honnorat N, Satterthwaite TD, Gur RE, Gur RC, Davatzikos C. sGraSP: A graph-based method for the derivation of subject-specific functional parcellations of the brain. J Neurosci Methods 2016; 277:1-20. [PMID: 27913211 DOI: 10.1016/j.jneumeth.2016.11.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 10/27/2016] [Accepted: 11/24/2016] [Indexed: 10/20/2022]
Abstract
BACKGROUND Resting-state fMRI (rs-fMRI) has emerged as a prominent tool for the study of functional connectivity. The identification of the regions associated with the different brain functions has received significant interest. However, most of the studies conducted so far have focused on the definition of a common set of regions, valid for an entire population. The variation of the functional regions within a population has rarely been accounted for. NEW METHOD In this paper, we propose sGraSP, a graph-based approach for the derivation of subject-specific functional parcellations. Our method generates first a common parcellation for an entire population, which is then adapted to each subject individually. RESULTS Several cortical parcellations were generated for 859 children being part of the Philadelphia Neurodevelopmental Cohort. The stability of the parcellations generated by sGraSP was tested by mixing population and subject rs-fMRI signals, to generate subject-specific parcels increasingly closer to the population parcellation. We also checked if the parcels generated by our method were better capturing a development trend underlying our data than the original parcels, defined for the entire population. COMPARISON WITH EXISTING METHODS We compared sGraSP with a simpler and faster approach based on a Voronoi tessellation, by measuring their ability to produce functionally coherent parcels adapted to the subject data. CONCLUSIONS Our parcellations outperformed the Voronoi tessellations. The parcels generated by sGraSP vary consistently with respect to signal mixing, the results are highly reproducible and the neurodevelopmental trend is better captured with the subject-specific parcellation, under all the signal mixing conditions.
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Affiliation(s)
- N Honnorat
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
| | - T D Satterthwaite
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Brain and Behavior Laboratory, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - R E Gur
- Brain and Behavior Laboratory, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - R C Gur
- Brain and Behavior Laboratory, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - C Davatzikos
- Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA.
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Mangin JF, Lebenberg J, Lefranc S, Labra N, Auzias G, Labit M, Guevara M, Mohlberg H, Roca P, Guevara P, Dubois J, Leroy F, Dehaene-Lambertz G, Cachia A, Dickscheid T, Coulon O, Poupon C, Rivière D, Amunts K, Sun Z. Spatial normalization of brain images and beyond. Med Image Anal 2016; 33:127-133. [DOI: 10.1016/j.media.2016.06.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Revised: 06/06/2016] [Accepted: 06/13/2016] [Indexed: 01/24/2023]
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Abstract
The 15 articles in this special issue on The Representation of Concepts illustrate the rich variety of theoretical positions and supporting research that characterize the area. Although much agreement exists among contributors, much disagreement exists as well, especially about the roles of grounding and abstraction in conceptual processing. I first review theoretical approaches raised in these articles that I believe are Quixotic dead ends, namely, approaches that are principled and inspired but likely to fail. In the process, I review various theories of amodal symbols, their distortions of grounded theories, and fallacies in the evidence used to support them. Incorporating further contributions across articles, I then sketch a theoretical approach that I believe is likely to be successful, which includes grounding, abstraction, flexibility, explaining classic conceptual phenomena, and making contact with real-world situations. This account further proposes that (1) a key element of grounding is neural reuse, (2) abstraction takes the forms of multimodal compression, distilled abstraction, and distributed linguistic representation (but not amodal symbols), and (3) flexible context-dependent representations are a hallmark of conceptual processing.
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Affiliation(s)
- Lawrence W Barsalou
- Institute of Neuroscience and Psychology, University of Glasgow, 58 Hillhead Street, Glasgow, G12 8QB, UK.
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255
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Large I, Bridge H, Ahmed B, Clare S, Kolasinski J, Lam WW, Miller KL, Dyrby TB, Parker AJ, Smith JET, Daubney G, Sallet J, Bell AH, Krug K. Individual Differences in the Alignment of Structural and Functional Markers of the V5/MT Complex in Primates. Cereb Cortex 2016; 26:3928-3944. [PMID: 27371764 PMCID: PMC5028002 DOI: 10.1093/cercor/bhw180] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Extrastriate visual area V5/MT in primates is defined both structurally by myeloarchitecture and functionally by distinct responses to visual motion. Myelination is directly identifiable from postmortem histology but also indirectly by image contrast with structural magnetic resonance imaging (sMRI). First, we compared the identification of V5/MT using both sMRI and histology in Rhesus macaques. A section-by-section comparison of histological slices with in vivo and postmortem sMRI for the same block of cortical tissue showed precise correspondence in localizing heavy myelination for V5/MT and neighboring MST. Thus, sMRI in macaques accurately locates histologically defined myelin within areas known to be motion selective. Second, we investigated the functionally homologous human motion complex (hMT+) using high-resolution in vivo imaging. Humans showed considerable intersubject variability in hMT+ location, when defined with myelin-weighted sMRI signals to reveal structure. When comparing sMRI markers to functional MRI in response to moving stimuli, a region of high myelin signal was generally located within the hMT+ complex. However, there were considerable differences in the alignment of structural and functional markers between individuals. Our results suggest that variation in area identification for hMT+ based on structural and functional markers reflects individual differences in human regional brain architecture.
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Affiliation(s)
- I Large
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
| | - H Bridge
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - B Ahmed
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
| | - S Clare
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - J Kolasinski
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - W W Lam
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - K L Miller
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - T B Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, 2650 Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - A J Parker
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
| | - J E T Smith
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
| | - G Daubney
- Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
| | - J Sallet
- Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
| | - A H Bell
- Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, UK
- MRC Cognition and Brain Sciences Unit, Cambridge, CB2 7EF, UK
| | - K Krug
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
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256
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Fan L, Li H, Zhuo J, Zhang Y, Wang J, Chen L, Yang Z, Chu C, Xie S, Laird AR, Fox PT, Eickhoff SB, Yu C, Jiang T. The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cereb Cortex 2016; 26:3508-26. [PMID: 27230218 PMCID: PMC4961028 DOI: 10.1093/cercor/bhw157] [Citation(s) in RCA: 1548] [Impact Index Per Article: 193.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.
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Affiliation(s)
| | - Hai Li
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Junjie Zhuo
- Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Yu Zhang
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Jiaojian Wang
- Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Liangfu Chen
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Zhengyi Yang
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Congying Chu
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Sangma Xie
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich 52425, Germany Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Tianzi Jiang
- Brainnetome Center National Laboratory of Pattern Recognition and CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China The Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
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257
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Schubert N, Axer M, Schober M, Huynh AM, Huysegoms M, Palomero-Gallagher N, Bjaalie JG, Leergaard TB, Kirlangic ME, Amunts K, Zilles K. 3D Reconstructed Cyto-, Muscarinic M2 Receptor, and Fiber Architecture of the Rat Brain Registered to the Waxholm Space Atlas. Front Neuroanat 2016; 10:51. [PMID: 27199682 PMCID: PMC4853377 DOI: 10.3389/fnana.2016.00051] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 04/18/2016] [Indexed: 12/25/2022] Open
Abstract
High-resolution multiscale and multimodal 3D models of the brain are essential tools to understand its complex structural and functional organization. Neuroimaging techniques addressing different aspects of brain organization should be integrated in a reference space to enable topographically correct alignment and subsequent analysis of the various datasets and their modalities. The Waxholm Space (http://software.incf.org/software/waxholm-space) is a publicly available 3D coordinate-based standard reference space for the mapping and registration of neuroanatomical data in rodent brains. This paper provides a newly developed pipeline combining imaging and reconstruction steps with a novel registration strategy to integrate new neuroimaging modalities into the Waxholm Space atlas. As a proof of principle, we incorporated large scale high-resolution cyto-, muscarinic M2 receptor, and fiber architectonic images of rat brains into the 3D digital MRI based atlas of the Sprague Dawley rat in Waxholm Space. We describe the whole workflow, from image acquisition to reconstruction and registration of these three modalities into the Waxholm Space rat atlas. The registration of the brain sections into the atlas is performed by using both linear and non-linear transformations. The validity of the procedure is qualitatively demonstrated by visual inspection, and a quantitative evaluation is performed by measurement of the concordance between representative atlas-delineated regions and the same regions based on receptor or fiber architectonic data. This novel approach enables for the first time the generation of 3D reconstructed volumes of nerve fibers and fiber tracts, or of muscarinic M2 receptor density distributions, in an entire rat brain. Additionally, our pipeline facilitates the inclusion of further neuroimaging datasets, e.g., 3D reconstructed volumes of histochemical stainings or of the regional distributions of multiple other receptor types, into the Waxholm Space. Thereby, a multiscale and multimodal rat brain model was created in the Waxholm Space atlas of the rat brain. Since the registration of these multimodal high-resolution datasets into the same coordinate system is an indispensable requisite for multi-parameter analyses, this approach enables combined studies on receptor and cell distributions as well as fiber densities in the same anatomical structures at microscopic scales for the first time.
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Affiliation(s)
- Nicole Schubert
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | - Markus Axer
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | - Martin Schober
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | - Anh-Minh Huynh
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | - Marcel Huysegoms
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | | | - Jan G. Bjaalie
- Institute of Basic Medical Sciences, University of OsloOslo, Norway
| | | | - Mehmet E. Kirlangic
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
- C. and O. Vogt Institute for Brain Research, Heinrich-Heine University DüsseldorfDüsseldorf, Germany
| | - Karl Zilles
- Institute of Neuroscience and Medicine 1, Research Centre JülichJülich, Germany
- Translational Brain Medicine, Jülich-Aachen Research AllianceAachen, Germany
- Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen UniversityAachen, Germany
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258
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A map of the human neocortex showing the estimated overall myelin content of the individual architectonic areas based on the studies of Adolf Hopf. Brain Struct Funct 2016; 222:465-480. [PMID: 27138385 PMCID: PMC5225164 DOI: 10.1007/s00429-016-1228-7] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 04/21/2016] [Indexed: 12/01/2022]
Abstract
During the period extending from 1910 to 1970, Oscar and Cécile Vogt and their numerous collaborators published a large number of myeloarchitectonic studies on the cortex of the various lobes of the human cerebrum. In a previous publication [Nieuwenhuys et al (Brain Struct Funct 220:2551–2573, 2015; Erratum in Brain Struct Funct 220: 3753–3755, 2015)], we used the data provided by the Vogt–Vogt school for the composition of a myeloarchitectonic map of the entire human neocortex. Because these data were derived from many different brains, a standard brain had to be introduced to which all data available could be transferred. As such the Colin 27 structural scan, aligned to the MNI305 template was selected. The resultant map includes 180 myeloarchitectonic areas, 64 frontal, 30 parietal, 6 insular, 17 occipital and 63 temporal. Here we present a supplementary map in which the overall density of the myelinated fibers in the individual architectonic areas is indicated, based on a meta-analysis of data provided by Adolf Hopf, a prominent collaborator of the Vogts. This map shows that the primary sensory and motor regions are densely myelinated and that, in general, myelination decreases stepwise with the distance from these primary regions. The map also reveals the presence of a number of heavily myelinated formations, situated beyond the primary sensory and motor domains, each consisting of two or more myeloarchitectonic areas. These formations were provisionally designated as the orbitofrontal, intraparietal, posterolateral temporal, and basal temporal dark clusters. Recently published MRI-based in vivo myelin content mappings show, with regard to the primary sensory and motor regions, a striking concordance with our map. As regards the heavily myelinated clusters shown by our map, scrutiny of the current literature revealed that correlates of all of these clusters have been identified in in vivo structural MRI studies and appear to correspond either entirely or largely to known cytoarchitectonic entities. Moreover, functional neuroimaging studies indicate that all of these clusters are involved in vision-related cognitive functions.
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Axer M, Strohmer S, Gräßel D, Bücker O, Dohmen M, Reckfort J, Zilles K, Amunts K. Estimating Fiber Orientation Distribution Functions in 3D-Polarized Light Imaging. Front Neuroanat 2016; 10:40. [PMID: 27147981 PMCID: PMC4835454 DOI: 10.3389/fnana.2016.00040] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Accepted: 03/29/2016] [Indexed: 11/13/2022] Open
Abstract
Research of the human brain connectome requires multiscale approaches derived from independent imaging methods ideally applied to the same object. Hence, comprehensible strategies for data integration across modalities and across scales are essential. We have successfully established a concept to bridge the spatial scales from microscopic fiber orientation measurements based on 3D-Polarized Light Imaging (3D-PLI) to meso- or macroscopic dimensions. By creating orientation distribution functions (pliODFs) from high-resolution vector data via series expansion with spherical harmonics utilizing high performance computing and supercomputing technologies, data fusion with Diffusion Magnetic Resonance Imaging has become feasible, even for a large-scale dataset such as the human brain. Validation of our approach was done effectively by means of two types of datasets that were transferred from fiber orientation maps into pliODFs: simulated 3D-PLI data showing artificial, but clearly defined fiber patterns and real 3D-PLI data derived from sections through the human brain and the brain of a hooded seal.
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Affiliation(s)
- Markus Axer
- Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany
| | - Sven Strohmer
- Jülich Supercomputing Centre, Institute for Advanced Simulation, Research Centre JülichJülich, Germany; Research Centre Jülich, Simulation Lab Neuroscience, Bernstein Facility for Simulation and Database Technology, Institute for Advanced SimulationJülich, Germany
| | - David Gräßel
- Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany
| | - Oliver Bücker
- Jülich Supercomputing Centre, Institute for Advanced Simulation, Research Centre Jülich Jülich, Germany
| | - Melanie Dohmen
- Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany
| | - Julia Reckfort
- Research Centre Jülich, Institute of Neuroscience and Medicine Jülich, Germany
| | - Karl Zilles
- Research Centre Jülich, Institute of Neuroscience and MedicineJülich, Germany; Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen UniversityAachen, Germany; JARA Jülich-Aachen Research Alliance, Translational Brain MedicineAachen, Germany
| | - Katrin Amunts
- Research Centre Jülich, Institute of Neuroscience and MedicineJülich, Germany; C. and O. Vogt Institute for Brain Research, Heinrich-Heine-University DüsseldorfDüsseldorf, Germany
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260
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Fan L, Li H, Yu S, Jiang T. Human Brainnetome Atlas and Its Potential Applications in Brain-Inspired Computing. LECTURE NOTES IN COMPUTER SCIENCE 2016. [DOI: 10.1007/978-3-319-50862-7_1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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